Eye contact norms create three recurring access barriers for visually impaired people in mixed-ability groups, reframing accessible design as support for explicit interaction contracts instead of gaze visibility.
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Artographer is a zoomable 2D embedding-based map for art exploration, evaluated in a study with 20 participants to surface values of Visibility, Agency, Serendipity, and Friction that challenge recommendation-driven media distribution.
SwitchMT uses adaptive task-switching in deep spiking Q-networks with active dendrites to reduce task interference in multi-task RL, achieving competitive Atari scores without added network complexity.
GSA-YOLO modifies YOLOv8n with structured sparsity via Group Lasso and Sparse Structure Selection plus Adaptive Knowledge Distillation, reporting 189.62 FPS and mAP50:95 gains of 2.4% and 1.8% on HiXray and PIDray datasets.
GA-S2S integrates T5 with RGAT to jointly process text and k-hop subgraph topology for knowledge graph link prediction, reporting up to 19% relative accuracy gain over seq2seq baselines on CoDEx.
Authors introduce MLM and CLM specialization methods that avoid memorizing identifiers in sensitive training data while aiming for a privacy-utility tradeoff on medical datasets.
A survey that organizes methods for cross-domain object detection into a taxonomy, analyzes domain shift across detection stages, and outlines persistent challenges.
citing papers explorer
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The Ambivalent Experience of Eye Contact for People with Visual Impairments: Mechanisms and Design Challenges
Eye contact norms create three recurring access barriers for visually impaired people in mixed-ability groups, reframing accessible design as support for explicit interaction contracts instead of gaze visibility.
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Artographer: a Curatorial Interface for Art Space Exploration
Artographer is a zoomable 2D embedding-based map for art exploration, evaluated in a study with 20 participants to surface values of Visibility, Agency, Serendipity, and Friction that challenge recommendation-driven media distribution.
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Scalable Multi-Task Learning through Spiking Neural Networks with Adaptive Task-Switching Policy for Intelligent Autonomous Agents
SwitchMT uses adaptive task-switching in deep spiking Q-networks with active dendrites to reduce task interference in multi-task RL, achieving competitive Atari scores without added network complexity.
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GSA-YOLO: A High-Efficiency Framework via Structured Sparsity and Adaptive Knowledge Distillation for Real-Time X-ray Security Inspection
GSA-YOLO modifies YOLOv8n with structured sparsity via Group Lasso and Sparse Structure Selection plus Adaptive Knowledge Distillation, reporting 189.62 FPS and mAP50:95 gains of 2.4% and 1.8% on HiXray and PIDray datasets.
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Leveraging Graph Structure in Seq2Seq Models for Knowledge Graph Link Prediction
GA-S2S integrates T5 with RGAT to jointly process text and k-hop subgraph topology for knowledge graph link prediction, reporting up to 19% relative accuracy gain over seq2seq baselines on CoDEx.
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Towards the Anonymization of the Language Modeling
Authors introduce MLM and CLM specialization methods that avoid memorizing identifiers in sensitive training data while aiming for a privacy-utility tradeoff on medical datasets.
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Generalization Under Scrutiny: Cross-Domain Detection Progresses, Pitfalls, and Persistent Challenges
A survey that organizes methods for cross-domain object detection into a taxonomy, analyzes domain shift across detection stages, and outlines persistent challenges.